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Bacterial promoter prediction: Selection of dynamic and static physical properties of DNA for reliable sequence classificationстатья Исследовательская статья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 10 июля 2019 г.
- Авторы: Ryasik A., Orlov M., Zykova E., Sorokin A., Ermak T.
- Журнал: Journal of Bioinformatics and Computational Biology
- Том: 16
- Номер: 1
- Год издания: 2018
- Издательство: Imperial College Press
- Местоположение издательства: United Kingdom
- Первая страница: 1840003
- DOI: 10.1142/S0219720018400036
- Аннотация: Predicting promoter activity of DNA fragment is an important task for computational biology. Approaches using physical properties of DNA to predict bacterial promoters have recently gained a lot of attention. To select an adequate set of physical properties for training a classifier, various characteristics of DNA molecule should be taken into consideration. Here, we present a systematic approach that allows us to select less correlated properties for classification by means of both correlation and cophenetic coefficients as well as concordance matrices. To prove this concept, we have developed the first classifier that uses not only sequence and static physical properties of DNA fragment, but also dynamic properties of DNA open states. Therefore, the best performing models with accuracy values up to 90% for all types of sequences were obtained. Furthermore, we have demonstrated that the classifier can serve as a reliable tool enabling promoter DNA fragments to be distinguished from promoter islands despite the similarity of their nucleotide sequences.
- Добавил в систему: Орлов Михаил Анатольевич